update multi_dot exposure rules (#36018)

python/paddle/__init__.py

@@ -103,7 +103,6 @@ from .tensor.linalg import histogram  # noqa: F401
 from .tensor.linalg import mv  # noqa: F401
 from .tensor.linalg import det  # noqa: F401
 from .tensor.linalg import slogdet  # noqa: F401
-from .tensor.linalg import multi_dot  # noqa: F401
 from .tensor.linalg import matrix_power  # noqa: F401
 from .tensor.linalg import svd  # noqa: F401
 from .tensor.linalg import solve  # noqa: F401

python/paddle/fluid/tests/unittests/test_multi_dot_op.py

@@ -198,32 +198,34 @@ class TestMultiDotOpError(unittest.TestCase):
                                          paddle.static.Program()):
             # The inputs type of multi_dot must be list matrix.
             input1 = 12
-            self.assertRaises(TypeError, paddle.multi_dot, [input1, input1])
+            self.assertRaises(TypeError, paddle.linalg.multi_dot,
+                              [input1, input1])
 
             # The inputs dtype of multi_dot must be float64, float64 or float16.
             input2 = paddle.static.data(
                 name='input2', shape=[10, 10], dtype="int32")
-            self.assertRaises(TypeError, paddle.multi_dot, [input2, input2])
+            self.assertRaises(TypeError, paddle.linalg.multi_dot,
+                              [input2, input2])
 
             # the number of tensor must be larger than 1
             x0 = paddle.static.data(name='x0', shape=[3, 2], dtype="float64")
-            self.assertRaises(ValueError, paddle.multi_dot, [x0])
+            self.assertRaises(ValueError, paddle.linalg.multi_dot, [x0])
 
             #the first tensor must be 1D or 2D
             x1 = paddle.static.data(name='x1', shape=[3, 2, 3], dtype="float64")
             x2 = paddle.static.data(name='x2', shape=[3, 2], dtype="float64")
-            self.assertRaises(ValueError, paddle.multi_dot, [x1, x2])
+            self.assertRaises(ValueError, paddle.linalg.multi_dot, [x1, x2])
 
             #the last tensor must be 1D or 2D
             x3 = paddle.static.data(name='x3', shape=[3, 2], dtype="float64")
             x4 = paddle.static.data(name='x4', shape=[3, 2, 2], dtype="float64")
-            self.assertRaises(ValueError, paddle.multi_dot, [x3, x4])
+            self.assertRaises(ValueError, paddle.linalg.multi_dot, [x3, x4])
 
             #the tensor must be 2D, except first and last tensor
             x5 = paddle.static.data(name='x5', shape=[3, 2], dtype="float64")
             x6 = paddle.static.data(name='x6', shape=[2], dtype="float64")
             x7 = paddle.static.data(name='x7', shape=[2, 2], dtype="float64")
-            self.assertRaises(ValueError, paddle.multi_dot, [x5, x6, x7])
+            self.assertRaises(ValueError, paddle.linalg.multi_dot, [x5, x6, x7])
 
 
 class APITestMultiDot(unittest.TestCase):
@@ -232,7 +234,7 @@ class APITestMultiDot(unittest.TestCase):
         with paddle.static.program_guard(paddle.static.Program()):
             x0 = paddle.static.data(name='x0', shape=[3, 2], dtype="float64")
             x1 = paddle.static.data(name='x1', shape=[2, 3], dtype='float64')
-            result = paddle.multi_dot([x0, x1])
+            result = paddle.linalg.multi_dot([x0, x1])
             exe = paddle.static.Executor(paddle.CPUPlace())
             data1 = np.random.rand(3, 2).astype("float64")
             data2 = np.random.rand(2, 3).astype("float64")
@@ -254,7 +256,7 @@ class APITestMultiDot(unittest.TestCase):
         input_array2 = np.random.rand(4, 3).astype("float64")
         data1 = paddle.to_tensor(input_array1)
         data2 = paddle.to_tensor(input_array2)
-        out = paddle.multi_dot([data1, data2])
+        out = paddle.linalg.multi_dot([data1, data2])
         expected_result = np.linalg.multi_dot([input_array1, input_array2])
         self.assertTrue(np.allclose(expected_result, out.numpy()))
 

python/paddle/tensor/__init__.py

@@ -387,6 +387,7 @@ tensor_method_func  = [ #noqa
            'bitwise_not',
            'broadcast_tensors',
            'uniform_',
+           'multi_dot',
            'solve',
 ]
 

python/paddle/tensor/linalg.py

@@ -975,8 +975,8 @@ def t(input, name=None):
         return out
 
     check_variable_and_dtype(
-        input, 'input', ['float16', 'float32', 'float64', 'int32', 'int64'],
-        'transpose')
+        input, 'input', ['float16', 'float32', 'float64', 'int32',
+                         'int64'], 'transpose')
 
     helper = LayerHelper('t', **locals())
     out = helper.create_variable_for_type_inference(input.dtype)
@@ -1360,7 +1360,7 @@ def det(x):
     Returns:
         y (Tensor):the determinant value of a square matrix or batches of square matrices.
 
-    Example: 
+    Examples:
         .. code-block:: python
 
         import paddle
@@ -1415,7 +1415,7 @@ def slogdet(x):
         y (Tensor): A tensor containing the sign of the determinant and the natural logarithm
         of the absolute value of determinant, respectively.
 
-    Example:
+    Examples:
     .. code-block:: python
 
         import paddle
@@ -1630,8 +1630,8 @@ def eigvals(x, name=None):
     """
 
     check_variable_and_dtype(x, 'dtype',
-                             ['float32', 'float64', 'complex64', 'complex128'],
-                             'eigvals')
+                             ['float32', 'float64', 'complex64',
+                              'complex128'], 'eigvals')
 
     x_shape = list(x.shape)
     if len(x_shape) < 2:
@@ -1657,7 +1657,7 @@ def multi_dot(x, name=None):
     """
     Multi_dot is an operator that calculates multiple matrix multiplications.
 
-    Supports inputs of float, double and float16 dtypes. This function does not
+    Supports inputs of float16(only GPU support), float32 and float64 dtypes. This function does not
     support batched inputs.
 
     The input tensor in [x] must be 2-D except for the first and last can be 1-D.
@@ -1699,7 +1699,7 @@ def multi_dot(x, name=None):
         B_data = np.random.random([4, 5]).astype(np.float32)
         A = paddle.to_tensor(A_data)
         B = paddle.to_tensor(B_data)
-        out = paddle.multi_dot([A, B])
+        out = paddle.linalg.multi_dot([A, B])
         print(out.numpy().shape)
         # [3, 5]
 
@@ -1710,7 +1710,7 @@ def multi_dot(x, name=None):
         A = paddle.to_tensor(A_data)
         B = paddle.to_tensor(B_data)
         C = paddle.to_tensor(C_data)
-        out = paddle.multi_dot([A, B, C])
+        out = paddle.linalg.multi_dot([A, B, C])
         print(out.numpy().shape)
         # [10, 7]
 
@@ -1998,8 +1998,8 @@ def pinv(x, rcond=1e-15, hermitian=False, name=None):
             helper = LayerHelper('pinv', **locals())
             dtype = x.dtype
             check_variable_and_dtype(
-                x, 'dtype', ['float32', 'float64', 'complex64', 'complex128'],
-                'pinv')
+                x, 'dtype', ['float32', 'float64', 'complex64',
+                             'complex128'], 'pinv')
 
             if dtype == paddle.complex128:
                 s_type = 'float64'